
PosePipe is a human pose estimation (HPE) pipeline designed to facilitate movement analysis from videos.
It uses DataJoint to manage relationships between algorithms, videos, and intermediate outputs.
Key features:
pip install pose_pipeline
Detailed installation instructions are provided to launch a DataJoint MySQL database and install OpenMMLab packages.
Use the Getting Started Notebook to start running your videos through the pose estimation framework.
VSCode is recommended for development.
Include the following in your .vscode/settings.json to enable consistent black formatting:
{
"python.formatting.blackArgs": [
"--line-length=120",
"--include='*py'",
"--exclude='*ipynb'",
"--extend-exclude='.env'",
"--extend-exclude='3rdparty/*'"
],
"editor.rulers": [120]
}
If you use this tool for research, please cite:
@misc{posepipe2024,
author = {R James Cotton},
title = {PosePipe: Open-Source Human Pose Estimation Pipeline for Clinical Research},
year = {2024},
howpublished = {\url{https://github.com/IntelligentSensingAndRehabilitation/PosePipeline}}
}
Python
95.9%
Jupyter Notebook
3.6%

PosePipe is a human pose estimation (HPE) pipeline designed to facilitate movement analysis from videos.
It uses DataJoint to manage relationships between algorithms, videos, and intermediate outputs.
Key features:
pip install pose_pipeline
Detailed installation instructions are provided to launch a DataJoint MySQL database and install OpenMMLab packages.
Use the Getting Started Notebook to start running your videos through the pose estimation framework.
VSCode is recommended for development.
Include the following in your .vscode/settings.json to enable consistent black formatting:
{
"python.formatting.blackArgs": [
"--line-length=120",
"--include='*py'",
"--exclude='*ipynb'",
"--extend-exclude='.env'",
"--extend-exclude='3rdparty/*'"
],
"editor.rulers": [120]
}
If you use this tool for research, please cite:
@misc{posepipe2024,
author = {R James Cotton},
title = {PosePipe: Open-Source Human Pose Estimation Pipeline for Clinical Research},
year = {2024},
howpublished = {\url{https://github.com/IntelligentSensingAndRehabilitation/PosePipeline}}
}
Python
95.9%
Jupyter Notebook
3.6%